摘要：According to several research circles, it is predicted that future wireless systems that employ smart antenna techniques would be more effective at using available spectrum and at building new networks at lower cost, while also improving service quality and allowing for cross-technology operation. These systems require constant monitoring in order to function properly, allowing users to apply machine learning algorithms to analyse large amounts of data from various antenna settings. Machine learning is a technique in which a machine learns and improves on its own, based on past data. These techniques enable the smart antenna target to be learned in an efficient, reliable, and adaptive manner. In this paper, the antenna array and antenna developed for the Internet of Things applications were highlighted. In this paper, we review how machine learning techniques can handle these applications effectively and what the concept of adaptive antenna is and when it can be used in this day and age characterized by the rapid development of information technology.
